Staff Machine Learning Engineer

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.

About the Opportunity

We are seeking a highly skilled and experienced Senior/ Staff Machine Learning Engineers to join our Risk Engineering Team, focusing on fraud detection, for example bot detection, credit card chargeback prevention, promotion abuse protection and so on. As a Tech Lead, you will be responsible for overseeing the end-to-end ML model development, deployment, and maintenance in production environments. You will also play a crucial role in building and maintaining the data validation pipeline and model performance monitoring systems. This position offers an exciting opportunity to lead a team of engineers while directly contributing to the growth of our machine learning infrastructure.

What You’ll Be Doing

• Lead the design, development, and deployment of end-to-end machine learning pipelines for production use, ensuring scalability, reliability, and performance.

• Design and implement a robust model performance monitoring system to track and evaluate the success of models in real-time, identifying areas for improvement.

• Manage and optimize the full lifecycle of ML models, including versioning, retraining, and monitoring model performance in production.

• Collaborate with cross-functional teams to implement and improve data validation pipelines, ensuring the integrity and quality of data used in ML models.

• Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.

• Provide technical leadership and mentorship to junior team members, supporting their professional development through coaching and code reviews.

What We Look For In You

• At least 5+ years of experience in Machine Learning Engineering

• Strong experience with ML Ops frameworks and tools (e.g., Flyte, Airflow, Kubeflow, MLflow, etc)

• Proficiency in Python and familiarity with Java.

• In-depth knowledge of data validation, data pipeline development, and performance monitoring systems.

• Extensive experience in deploying and managing machine learning models in production environments

• Solid understanding of CI/CD practices for machine learning workflows.

• Experience with SQL and familiarity with common data products such as PostgreSQL, DynamoDB, Kafka, and Redis.

• Familiarity with A/B testing, model drift detection, and advanced monitoring techniques.

• Strong problem-solving skills and ability to work in a fast-paced environment.

• Excellent communication and collaboration skills.

• Proven experience coaching and mentoring junior engineers.

• Familiar with at least one major cloud services, like AWS, CGP, Azure or Alicloud

Nice to Haves

• Experience in fraud detection, specifically in areas like bot detection, credit card chargeback prevention, and promotion abuse protection, is highly desirable.